Locating Hydrologically Unsustainable Areas for Supporting Ecological Restoration in China's Drylands

中国 恢复生态学 生态学 地理 环境科学 环境资源管理 生物 考古
作者
Fu F,Shuai Wang,Xutong Wu,Fengsi Wei,Peng Chen,José M. Grünzweig
出处
期刊:Earth’s Future [American Geophysical Union]
卷期号:12 (3)
标识
DOI:10.1029/2023ef004216
摘要

Abstract China has undertaken extensive ecological restoration (ER) projects since the late 1970s in drylands, dominating the greening of drylands. The greening, especially ER‐induced, can affect regional water availability and even cause hydrological unsustainability (i.e., lead to a negative shift in ecosystem water supply and demand balances). However, there is still limited research on accurately identifying the hydrologically unsustainable greening areas (GA) in China's drylands. Here, we developed an ecosystem water supply‐demand indicator, namely, the water self‐sufficiency (WSS), defined as the ratio of water availability to precipitation. Using remote sensing and multisource synthesis data sets combined with trend analysis and time series detection, we conducted a spatially explicit assessment of the hydrological sustainability risk of greening in China's drylands in the context of ER projects over the period 1987–2015. The results showed that 17.15% (6.36 × 10 4 km 2 ) of the GA faced a negative shift in the WSS (indicating hydrological unsustainability), mainly in Inner Mongolia, Shanxi, and Xinjiang provinces, driven by evapotranspiration. Moreover, 29.34% (1.09 × 10 5 km 2 ) of the GA, whose area is roughly double that of hydrologically unsustainable GA, exhibited a potential water shortage with a significant WSS decline (−0.014 yr −1 ), concentrated in Inner Mongolia, Shaanxi, and Gansu provinces. The reliability of our findings was demonstrated through previous studies at the local scale and an analysis of soil moisture changes. Our findings offer precise grid‐scale identification of the hydrologically unsustainable GA, providing more specific spatial guidance for ER implementation and adaptation in China's drylands.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
孙勇发完成签到,获得积分10
刚刚
郭逍遥完成签到,获得积分10
1秒前
1秒前
Orange应助科研通管家采纳,获得10
2秒前
江户川完成签到,获得积分10
4秒前
大胆盼烟发布了新的文献求助10
4秒前
7秒前
Ada完成签到 ,获得积分10
7秒前
乐观的傲芙完成签到,获得积分10
8秒前
正直听白完成签到,获得积分10
9秒前
10秒前
kkkkk发布了新的文献求助10
12秒前
14秒前
guo完成签到 ,获得积分10
15秒前
Rui发布了新的文献求助10
16秒前
彭于晏应助Buster采纳,获得10
17秒前
19秒前
志轩完成签到,获得积分10
19秒前
20秒前
小太阳哈哈完成签到 ,获得积分10
20秒前
sodarday完成签到,获得积分10
21秒前
榴莲奶黄包完成签到,获得积分20
21秒前
orixero应助Ssshumiao采纳,获得10
23秒前
25秒前
sodarday发布了新的文献求助10
25秒前
hahhh7完成签到,获得积分10
25秒前
25秒前
RADIUM三餐都要吃肉完成签到,获得积分10
27秒前
可爱的函函应助yuyuyuan采纳,获得10
27秒前
方方完成签到,获得积分10
27秒前
jzs完成签到 ,获得积分0
28秒前
南亭完成签到,获得积分0
28秒前
wuli林完成签到,获得积分10
30秒前
30秒前
shirely发布了新的文献求助10
31秒前
ymx完成签到,获得积分10
32秒前
珠珠完成签到 ,获得积分10
32秒前
海开心呀完成签到,获得积分10
37秒前
41秒前
Meng完成签到,获得积分10
43秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359619
求助须知:如何正确求助?哪些是违规求助? 8173565
关于积分的说明 17214837
捐赠科研通 5414599
什么是DOI,文献DOI怎么找? 2865578
邀请新用户注册赠送积分活动 1842883
关于科研通互助平台的介绍 1691124